Praharshita Krishna's repositories
github-organizations-page
search organizations in Github :octocat: by using the Github GraphQL API
NotesOnCausality
Personal notes on causality, causal machine learning, causal projects for project based learning.
AI-Expert-Roadmap
Roadmap to becoming an Artificial Intelligence Expert in 2022
applied-ml
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
awesome-causality-algorithms
An index of algorithms for learning causality with data
awesome-ospo
Curated list of awesome tools for managing open source programs
causal-learn
Causal Discovery for Python. Translation and extension of the Tetrad Java code.
Causal_Reading_Group
We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.
causalai
Salesforce CausalAI Library: A Fast and Scalable framework for Causal Analysis of Time Series and Tabular Data
causalml
Uplift modeling and causal inference with machine learning algorithms
computational-thinking
Course 18.S191 at MIT, Fall 2022 - Introduction to computational thinking with Julia
courses
This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)
cs-video-courses
List of Computer Science courses with video lectures.
DataScienceImplementDumps
Everything I am exploring in Tensorflow/Pytorch/SciPy etc.
Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
DSAlgo_POW
Proof of work - Data structures and Algorithms
EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal in
Econometrics_DataScience_POW
Proof of work - Econometrics + Data Science
eddiejaoude
Custom GitHub profile for Eddie Jaoude
HistoryOfComputerScience
Creating a primer to the development of computer science.
keras-nlp
Modular Natural Language Processing workflows with Keras
numpyro
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
pywhy-llm
Experimental library integrating LLM capabilities to support causal analyses
qss
Supplementary Materials for ``Quantitative Social Science: An Introduction''
Visual-Language-Understanding
Personal repository for notes on vision language models with small proof-of-concept implementations for my own understanding